D.M. Yan, J. Guo, X. Jia, X. Zhang, P. Wonka
Computer Graphics Forum, volume 33, issue 5, pp. 167-176, (2014)
In this paper, we present a novel method for surface sampling and
remeshing with good blue-noise properties. Our approach is based on the
farthest point optimization (FPO), a relaxation technique that generates
high quality blue-noise point sets in 2D. We propose two important
generalizations of the original FPO framework: adaptive sampling and
sampling on surfaces. A simple and efficient algorithm for accelerating
the FPO framework is also proposed. Experimental results show that the
generalized FPO generates point sets with excellent blue-noise
properties for adaptive and surface sampling. Furthermore, we
demonstrate that our remeshing quality is superior to the current
state-of-theߚart approaches.